Social networking systems may use profiles to connect people who might like to meet each other. The idea of connecting strangers or friends who might not otherwise meet is powerful. However, the value of these systems may be limited by the rudimentary methods used to make matches: basic preference characteristics such as a common business relationship, social relationship, family relationship, compatible physical characteristics, or self-declared preferences for food, clothing, leisure activities, sports, entertainment, music, art, etc.
A key problem with such basic social networking systems is a lack of verifiability and authenticity of match criteria, leading to a surfeit of low quality matches. Too many low quality matches can lead to a loss of faith in the entire system, poor usability overall, and questions of trust when you meet people (or connect to entities) through such matching criteria.
Another problem is that such systems force users to do the tedious work of creating self-generated profiles by inputting personal information, akin to filling out a questionnaire. This creates two problems: inconvenience for participants and a lack of standards that everyone can trust. First, many people are busy, or lazy. Any system that relies on its users creating and updating multivariable profiles is inherently flawed. Too many people will let their profiles become stale. Second, people have different standards when it comes to self-declared information. I may think I am a connoisseur of wine, whereas by someone else's definition I am a novice. In addition, the information I supply in creating my profile may not be useful for distinguishing me from other users in the system. For instance, I may mention that I am a Red Sox fan in my self-generated profile. However, this information may not useful for distinguishing among the thousands of other Red Sox fans in the Boston area. Subtleties are lost. For example, I may be a diehard fan and want to meet others who, like me, have season tickets. In other words, gradation information can be important and is sometimes either lost or mischaracterized with self-generated profiling.
What is desired therefore is an improved system and method that adds accountability and standards to user profiles, ideally one which does not burden the user with the cumbersome task of building and maintaining a profile. What is also desired is an improved system and method for location- and context-based matching and filtering of users. What is also desired is an improved system that allows not only people to be matched with other people but also people to be matched with “entities”, such as restaurants, bars, organizations, parties, stores, and even cities.